The term ‘Big Data’ has been around since the 1990s. However, we do not know who the first person to use the term was. John R. Mashey is credited with making the term popular. In reality, big data is not new and not something that has garnered attention over the past few decades. Over the last few centuries, different data analytics and analysis techniques have been developed to pave the way for smooth and informed decision-making.
With advancements in technology, the world of big data has evolved and become very streamlined. Data analytics in business has become very common as more and more companies understand the increasing need to harness data and extract valuable insights from it. The volume of data generated by omnichannel and e-commerce systems, IoT-connected devices, and a plethora of business applications is growing exponentially. This is why, data analytics in business is an expanding field, creating more opportunities for data analysts and scientists.
There are plenty of benefits of data analytics in business. In this article, we will explore these benefits and get a better understanding of why data analytics in business is so important. Before we talk about the benefits of data analytics in business, we should first know what big data is.
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What is big data?
As the name suggests, big data primarily refers to mammoth and complex data sets that are complex to be dealt with by conventional data processing software and solutions. Now, big data analytics assesses huge volumes of data to find correlations, patterns, and other critical information to improve decision-making.
Benefits of data analytics in business
1. Improved insights regarding customer behavior
When businesses rely on data to understand the pulse of their customers, they gather data from different sources. Big data sources that highlight customers include:
- Social media activity
- Computer cookies
- Data from external and internal surveys
- External sources including financial transactions and credit reports
- Traditional sources including support calls, purchases, and customer data
Digital marketplaces increasingly rely on clickstream analysis of the e-commerce activities of their customers. It provides insights into how customers or site visitors are navigating through different menus and pages to look for products and services. E-commerce companies can view which items were added/deleted to carts and even abandoned carts wherein a purchase was not completed. This type of data enables companies to understand what their customers are likely to buy even if they do not make a purchase.
While online stores have this advantage, even brick and mortar stores can extract precious clues by analyzing videos to find out how their visitors navigate through a physical store.
2. Better understanding of the market
Similar to how big data equips companies to understand their customer’s shopping behavior, it also sheds light on market dynamics. For example, social media is a treasure trove of market intelligence for various product categories including vacation rentals to breakfast cereals. Today, for any type of commercial transaction, there are customers out there who are sharing their recommendations, experiences, and preferences. Their opinion on the internet is invaluable for marketers.
Apart from assisting with competitive analysis, big data can also play a key role in product development.
3. Smarter audience targeting and recommendations
We have made peace with the fact that recommendation engines have become a vital part of our lives. What we may have missed is their evolution ever since big data analytics has set foot in the business world. At some stage, the predictive analysis used to make engine recommendations was pretty straightforward. There was a string of rules that found those common items in market baskets. Even today, you are likely to find these features on e-commerce websites which tell us that customers who have purchased an iPhone, have also purchased an iWatch.
Today, new recommendation systems have become smarter and pick up even the smallest of nuances of online shopping. Besides, they are not restricted only to e-commerce anymore. For example, a waiter at a restaurant’s recommendations may be data-driven, derived from data from a point of sale system. Modern-day point-of-sale systems evaluate popular combos, social media trends, high-profit items, and stock levels in the pantry. In addition, when customers share a picture of their meal on social media, more data is being fed into big data engines.
Today, even online streaming platforms use even more advanced analysis techniques. Most platforms do not ask customers what they want to see next, displaying the next selection even before a song of a movie is finished.
4. Innovation-driven by data
Innovation requires forward-thinking, an understanding of what can be achieved with the resources available, and getting a grip on what customers want. Innovation also requires a great amount of effort to identify subject areas that open up new opportunities in a particular industry.
Today, thanks to state-of-the-art big data technologies and tools, research and development have improved significantly. This, in return, has led to better and seamless development of novel services and products. At times, the data that is cleansed, governed, prepared, and shared is a product on its own. For example, the London Stock Exchange makes more money from selling analysis and data than from securities trading.
Human elements will continue to play an important in producing fresh insights even when the best big data platforms are available. Data scientists, BI analysts, and analytics professionals will become increasingly relevant in the future as they will be responsible for identifying industry trends and other patterns.
Benefits of big data in business are worth it
There are plenty of opportunities in the Big Data industry and it is a good time to leverage the benefits of big data in the business to stay ahead of the competition. Futuristic, data-driven, and smart players in the market are increasingly relying upon new big data technologies to derive accurate consumer insights, automate processes, and organize complex organizational operations.
A majority of the companies are using real-time information to pave the way for swift and informed decision-making. We hope by now you are convinced that big data analysis in business is important. So what are you waiting for? Start introducing data analytics to your business and stay connected with industry trends and understand your customers like never before.
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